Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
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Updated
Apr 28, 2025 - Python
Simulation refers to the process of creating a virtual model of a real-world system to study its behavior and performance under various conditions. This topic covers the principles, methodologies, and applications of simulation in fields such as engineering, science, healthcare, and social sciences. Simulations can range from simple models to complex, interactive environments, allowing researchers and practitioners to test hypotheses, train individuals, and predict outcomes without the risks or costs associated with real-world experiments. The topic also explores different types of simulation software and tools, as well as best practices for designing and validating simulations.
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
A python module for scientific analysis of 3D data based on VTK and Numpy
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Cryptocurrency trading bot with a graphical user interface with support for simulations, backtests, optimizations, and running live bots.
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Open-source, graph-based Python code generator and analysis toolbox for dynamical systems (pre-implemented and custom models). Most pre-implemented models belong to the family of neural population models.
The open-source particle-in-cell post-processor.
Negative Mass N-body Simulation Codes
Short python samples of recreational mathematics.
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